Prenatal pharmacogenomics: a promising area for research.

Pharmacogenomics J. 2016 May 10;

Authors: Dorfman EH, Cheng EY, Hebert MF, Thummel KE, Burke W

Abstract
Clinical applications of prenatal genetic screening currently focus on detection of aneuploidy and other genetic diseases in the developing fetus. Growing evidence suggests that the fetal genome may also be informative about fetal exposures through contributions to placental transport as well as placental and fetal metabolism. Possible clinical applications of prenatal pharmacogenomic screening include prospective optimization of medication selection and dosage, as well as retrospective assessment of whether a fetus was previously exposed to significant risk. Newly available noninvasive methods of prenatal genetic screening mean that relevant fetal genotypes could be made available to obstetricians for use in management of a current pregnancy. This promising area for research merits more attention than it has thus far received.The Pharmacogenomics Journal advance online publication, 10 May 2016; doi:10.1038/tpj.2016.33.

PMID: 27168097 [PubMed - as supplied by publisher]

Hematopoietic progenitor cell mobilization is more robust in healthy African American compared to Caucasian donors and is not affected by the presence of sickle cell trait.

Transfusion. 2016 May;56(5):1058-1065

Authors: Panch SR, Yau YY, Fitzhugh CD, Hsieh MM, Tisdale JF, Leitman SF

Abstract
BACKGROUND: Granulocyte-colony-stimulating factor (G-CSF)-stimulated hematopoietic progenitor cells (HPCs) collected by apheresis have become the predominant graft source for HPC transplantation in adults. Among healthy allogeneic donors, demographic characteristics (age, sex, body mass index [BMI]) and baseline hematologic counts affect HPC mobilization, leading to variability in CD34+ apheresis yields. Racial differences in HPC mobilization are less well characterized.
STUDY DESIGN AND METHODS: We retrospectively analyzed data from 1096 consecutive G-CSF-stimulated leukapheresis procedures in healthy allogeneic African American (AA) or Caucasian donors.
RESULTS: In a multivariate analysis, after adjusting for age, sex, BMI, baseline platelet and mononuclear cell counts, and daily G-CSF dose, peak CD34+ cell mobilization was significantly higher among AAs (n = 215) than Caucasians (n = 881; 123 ± 87 × 10(6) cells/L vs. 75 ± 47 × 10(6) cells/L; p < 0.0001). A ceiling effect was observed with increasing G-CSF dose (10 µg/kg/day vs. 16 µg/kg/day) in AAs (123 ± 88 × 10(6) cells/L vs. 123 ± 87 × 10(6) cells/L) but not in Caucasians (74 ± 46 × 10(6) cells/L vs. 93 ± 53 × 10(6) cells/L; p < 0.001). In AA donors, the presence of sickle cell trait (SCT; n = 41) did not affect CD34+ mobilization (peak CD34+ 123 ± 91 × 10(6) cells/L vs. 107 ± 72 × 10(6) cells/L, HbAS vs. HbAA; p = 0.34). Adverse events were minimal and similar across race.
CONCLUSIONS: AAs demonstrated significantly better CD34 mobilization responses to G-CSF than Caucasians. This was independent of other demographic and hematologic variables. Studying race-associated pharmacogenomics in relation to G-CSF may improve dosing strategies. Adverse event profile and CD34 mobilization were similar in AA donors with and without SCT. Our findings suggest that it would be safe to include healthy AA donors with SCT in unrelated donor registries.

PMID: 27167356 [PubMed - as supplied by publisher]

Recent advances and future applications of microfluidic live-cell microarrays.

Biotechnol Adv. 2015 Nov 1;33(6 Pt 1):948-61

Authors: Rothbauer M, Wartmann D, Charwat V, Ertl P

Abstract
Microfluidic live-cell microarrays show much promise as screening tools for biomedical research because they could shed light on key biological processes such as cell signaling and cell-to-cell and cell-to-substrate dynamic responses. While miniaturization reduces the need for expensive clinical grade reagents, the integration of functional components including micropumps, biosensors, actuators, mixers and gradient generators results in improved assay reliability, reproducibility and well-defined cell culture conditions. The present review addresses recent technological advances in microfluidic live-cell microarray technology with a special focus on the applications of microfluidic single-cell, multi-cell and 3D cell microarrays.

PMID: 26133396 [PubMed - indexed for MEDLINE]

The microbiome-immune-host defense barrier complex (microimmunosome) and developmental programming of noncommunicable diseases.

Reprod Toxicol. 2016 May 7;

Authors: R Dietert R

Abstract
Through its role as gatekeeper and filter to the external world, the microbiome affects developmental programming of physiological systems including the immune system. In turn, the immune system must tolerate, personalize, and prune the microbiome. Immune and host barrier status in early life significantly effects everything from embryo viability and pregnancy duration to the likelihood of misregulated inflammation, and risk of noncommunicable diseases (NCDs). Since the programming of and interactions among the microbiome, the host defense barrier, and the immune system can affect inflammation-driven health risks across the lifespan, a systems biology-type understanding of these three biological components may be useful. Here, I consider the potential utility of focusing on programming of a newly-defined systems biology unit termed the "microimmunosome."

PMID: 27167696 [PubMed - as supplied by publisher]

Sparse factor model for co-expression networks with an application using prior biological knowledge.

Stat Appl Genet Mol Biol. 2016 May 11;

Authors: Blum Y, Houée-Bigot M, Causeur D

Abstract
Inference on gene regulatory networks from high-throughput expression data turns out to be one of the main current challenges in systems biology. Such networks can be very insightful for the deep understanding of interactions between genes. Because genes-gene interactions is often viewed as joint contributions to known biological mechanisms, inference on the dependence among gene expressions is expected to be consistent to some extent with the functional characterization of genes which can be derived from ontologies (GO, KEGG, …). The present paper introduces a sparse factor model as a general framework either to account for a prior knowledge on joint contributions of modules of genes to latent biological processes or to infer on the corresponding co-expression network. We propose an ℓ1 - regularized EM algorithm to fit a sparse factor model for correlation. We demonstrate how it helps extracting modules of genes and more generally improves the gene clustering performance. The method is compared to alternative estimation procedures for sparse factor models of relevance networks in a simulation study. The integration of a biological knowledge based on the gene ontology (GO) is also illustrated on a liver expression data generated to understand adiposity variability in chicken.

PMID: 27166726 [PubMed - as supplied by publisher]

Many-molecule encapsulation by an icosahedral shell.

Elife. 2016 May 11;5

Authors: Perlmutter JD, Mohajerani F, Hagan MF

Abstract
We computationally study how an icosahedral shell assembles around hundreds of molecules. Such a process occurs during the formation of the carboxysome, a bacterial microcompartment that assembles around many copies of the enzymes ribulose 1,5-bisphosphate carboxylase/oxygenase and carbonic anhydrase to facilitate carbon fixation in cyanobacteria. Our simulations identify two classes of assembly pathways leading to encapsulation of many-molecule cargoes. In one, shell assembly proceeds concomitantly with cargo condensation. In the other, the cargo first forms a dense globule; then, shell proteins assemble around and bud from the condensed cargo complex. Although the model is simplified, the simulations predict intermediates and closure mechanisms not accessible in experiments, and show how assembly can be tuned between these two pathways by modulating protein interactions. In addition to elucidating assembly pathways and critical control parameters for microcompartment assembly, our results may guide the reengineering of viruses as nanoreactors that self-assemble around their reactants.

PMID: 27166515 [PubMed - as supplied by publisher]

Computational modeling approaches in gonadotropin signaling.

Theriogenology. 2016 Apr 20;

Authors: Ayoub MA, Yvinec R, Crépieux P, Poupon A

Abstract
Follicle-stimulating hormone and LH play essential roles in animal reproduction. They exert their function through binding to their cognate receptors, which belong to the large family of G protein-coupled receptors. This recognition at the plasma membrane triggers a plethora of cellular events, whose processing and integration ultimately lead to an adapted biological response. Understanding the nature and the kinetics of these events is essential for innovative approaches in drug discovery. The study and manipulation of such complex systems requires the use of computational modeling approaches combined with robust in vitro functional assays for calibration and validation. Modeling brings a detailed understanding of the system and can also be used to understand why existing drugs do not work as well as expected, and how to design more efficient ones.

PMID: 27165991 [PubMed - as supplied by publisher]

The Voice of Chinese Health Consumers: A Text Mining Approach to Web-Based Physician Reviews.

J Med Internet Res. 2016;18(5):e108

Authors: Hao H, Zhang K

Abstract
BACKGROUND: Many Web-based health care platforms allow patients to evaluate physicians by posting open-end textual reviews based on their experiences. These reviews are helpful resources for other patients to choose high-quality doctors, especially in countries like China where no doctor referral systems exist. Analyzing such a large amount of user-generated content to understand the voice of health consumers has attracted much attention from health care providers and health care researchers.
OBJECTIVE: The aim of this paper is to automatically extract hidden topics from Web-based physician reviews using text-mining techniques to examine what Chinese patients have said about their doctors and whether these topics differ across various specialties. This knowledge will help health care consumers, providers, and researchers better understand this information.
METHODS: We conducted two-fold analyses on the data collected from the "Good Doctor Online" platform, the largest online health community in China. First, we explored all reviews from 2006-2014 using descriptive statistics. Second, we applied the well-known topic extraction algorithm Latent Dirichlet Allocation to more than 500,000 textual reviews from over 75,000 Chinese doctors across four major specialty areas to understand what Chinese health consumers said online about their doctor visits.
RESULTS: On the "Good Doctor Online" platform, 112,873 out of 314,624 doctors had been reviewed at least once by April 11, 2014. Among the 772,979 textual reviews, we chose to focus on four major specialty areas that received the most reviews: Internal Medicine, Surgery, Obstetrics/Gynecology and Pediatrics, and Chinese Traditional Medicine. Among the doctors who received reviews from those four medical specialties, two-thirds of them received more than two reviews and in a few extreme cases, some doctors received more than 500 reviews. Across the four major areas, the most popular topics reviewers found were the experience of finding doctors, doctors' technical skills and bedside manner, general appreciation from patients, and description of various symptoms.
CONCLUSIONS: To the best of our knowledge, our work is the first study using an automated text-mining approach to analyze a large amount of unstructured textual data of Web-based physician reviews in China. Based on our analysis, we found that Chinese reviewers mainly concentrate on a few popular topics. This is consistent with the goal of Chinese online health platforms and demonstrates the health care focus in China's health care system. Our text-mining approach reveals a new research area on how to use big data to help health care providers, health care administrators, and policy makers hear patient voices, target patient concerns, and improve the quality of care in this age of patient-centered care. Also, on the health care consumer side, our text mining technique helps patients make more informed decisions about which specialists to see without reading thousands of reviews, which is simply not feasible. In addition, our comparison analysis of Web-based physician reviews in China and the United States also indicates some cultural differences.

PMID: 27165558 [PubMed - in process]

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Unexploited Antineoplastic Effects of Commercially Available Anti-Diabetic Drugs.

Pharmaceuticals (Basel). 2016;9(2)

Authors: Papanagnou P, Stivarou T, Tsironi M

Abstract
The development of efficacious antitumor compounds with minimal toxicity is a hot research topic. Numerous cancer cell targeted agents are evaluated daily in laboratories for their antitumorigenicity at the pre-clinical level, but the process of their introduction into the market is costly and time-consuming. More importantly, even if these new antitumor agents manage to gain approval, clinicians have no former experience with them. Accruing evidence supports the idea that several medications already used to treat pathologies other than cancer display pleiotropic effects, exhibiting multi-level anti-cancer activity and chemosensitizing properties. This review aims to present the anticancer properties of marketed drugs (i.e., metformin and pioglitazone) used for the management of diabetes mellitus (DM) type II. Mode of action, pre-clinical in vitro and in vivo or clinical data as well as clinical applicability are discussed here. Given the precious multi-year clinical experience with these non-antineoplastic drugs their repurposing in oncology is a challenging alternative that would aid towards the development of therapeutic schemes with less toxicity than those of conventional chemotherapeutic agents. More importantly, harnessing the antitumor function of these agents would save precious time from bench to bedside to aid the fight in the arena of cancer.

PMID: 27164115 [PubMed - as supplied by publisher]

Punctuated evolution and transitional hybrid network in an ancestral cell cycle of fungi.

Elife. 2016;5

Authors: Medina EM, Turner JJ, Gordân R, Skotheim JM, Buchler NE

Abstract
Although cell cycle control is an ancient, conserved, and essential process, some core animal and fungal cell cycle regulators share no more sequence identity than non-homologous proteins. Here, we show that evolution along the fungal lineage was punctuated by the early acquisition and entrainment of the SBF transcription factor through horizontal gene transfer. Cell cycle evolution in the fungal ancestor then proceeded through a hybrid network containing both SBF and its ancestral animal counterpart E2F, which is still maintained in many basal fungi. We hypothesize that a virally-derived SBF may have initially hijacked cell cycle control by activating transcription via the cis-regulatory elements targeted by the ancestral cell cycle regulator E2F, much like extant viral oncogenes. Consistent with this hypothesis, we show that SBF can regulate promoters with E2F binding sites in budding yeast.

PMID: 27162172 [PubMed - in process]

Global de novo protein-protein interactome elucidates interactions of drought responsive proteins in horsegram (Macrotyloma uniflorum).

J Proteome Res. 2016 May 10;

Authors: Bhardwaj J, Gangwar I, Panzade GP, Shankar R, Yadav SK

Abstract
Inspired by the availability of de novo transcriptome of horsegram (Macrotyloma uniflorum) and recent developments in systems biology studies, first ever global protein-protein interactome (PPI) map was constructed for this highly drought tolerant legume. Large-scale studies of PPIs and the constructed database would provide rationale behind the interplay at cascading translational levels for drought stress adaptive mechanisms in horsegram. Using a bidirectional approach (interolog and domain-based), a high confidence interactome map and database for horsegram was constructed. Available transcriptomic information for shoot and root tissues of a sensitive genotype (M-191; genotype 1) and a drought tolerant (M-249; genotype 2) of horsegram was utilized to draw comparative PPI sub-networks under drought stress. High confidence 6804 interactions were predicted among 1812 proteins covering about one-fourth of the horsegram proteome. Highest number of interactions (33.86%) in horsegram interactome matched with Arabidopsis PPI data. Top five hub nodes mostly included ubiquitin and heat shock related proteins. Higher numbers of PPIs were found to be responsive in shoot tissue (416) and root tissue (2228) of genotype 2 compared to shoot tissue (136) and root tissue (579) of genotype 1. Characterization of PPIs using gene ontology analysis revealed that kinase and transferase activities involved in signal transduction, cellular processes, nucleocytoplasmic transport, protein ubiquitination and localization of molecules were most responsive to drought stress. Hence, these could be framed in stress adaptive mechanisms of horsegram. Being the first legume global PPI map, it would provide new insights in gene and protein regulatory networks for drought stress tolerance mechanisms in horsegram. Information compiled in form of database (MauPIR) will provide the much needed high confidence systems biology information for horsegram genes, proteins and involved processes. This information would ease the effort and increase the efficacy for similar studies on other legumes. Public access is available at http://14.139.59.221/MauPIR/.

PMID: 27161830 [PubMed - as supplied by publisher]

Proteome-wide alterations on adipose tissue from obese patients as age-, diabetes- and gender-specific hallmarks.

Sci Rep. 2016;6:25756

Authors: Gómez-Serrano M, Camafeita E, García-Santos E, López JA, Rubio MA, Sánchez-Pernaute A, Torres A, Vázquez J, Peral B

Abstract
Obesity is a main global health issue and an outstanding cause of morbidity and mortality predisposing to type 2 diabetes (T2DM) and cardiovascular diseases. Huge research efforts focused on gene expression, cellular signalling and metabolism in obesity have improved our understanding of these disorders; nevertheless, to bridge the gap between the regulation of gene expression and changes in signalling/metabolism, protein levels must be assessed. We have extensively analysed visceral adipose tissue from age-, T2DM- and gender-matched obese patients using high-throughput proteomics and systems biology methods to identify new biomarkers for the onset of T2DM in obesity, as well as to gain insight into the influence of aging and gender in these disorders. About 250 proteins showed significant abundance differences in the age, T2DM and gender comparisons. In diabetic patients, remarkable gender-specific hallmarks were discovered regarding redox status, immune response and adipose tissue accumulation. Both aging and T2DM processes were associated with mitochondrial remodelling, albeit through well-differentiated proteome changes. Systems biology analysis highlighted mitochondrial proteins that could play a key role in the age-dependent pathophysiology of T2DM. Our findings could serve as a framework for future research in Translational Medicine directed at improving the quality of life of obese patients.

PMID: 27160966 [PubMed - in process]

Understanding the Metabolic Consequences of Human Arylsulfatase A Deficiency through a Computational Systems Biology Study.

Cent Nerv Syst Agents Med Chem. 2016 May 10;

Authors: Echeverri Olga Y, Salazar Diego A, Rodriguez-Lopez A, Janneth G, Almeciga-Diaz Carlos J, Barrera Luis A

Abstract
The nervous system is responsible for the communication between the organism and its environment. This task is possible by the presence of the myelin sheath, which is a double membrane formed by about 75% lipids and 25% proteins. The sulfatide represents one of the main lipids of the myelin band; its degradation is catabolized by the enzyme Arylsulfatase A (ARSA), to generated galactosylceramide. Mutations affecting ARSA function lead to the neurodegenerative disease Metachromatic Leukodystrophy. This disease is characterized by accumulation of sulfatide within the band of myelin affecting its functionality. The biochemical consequences of ARSA deficiency are not well understood yet. In this paper, we used an in-silico systems-biology approach to model the biochemical consequences of ARSA deficiency within a general human metabolic network (Recon2) and a glia cellular model. We expected that ARSA deficiency mainly affected the glycosphingolipid pathways. However, the results suggest that mitochondrial metabolism and amino acid transport were the main reactions affected within both cellular models. In the glia cell model, it was highlighted the high number of affected reactions of neurotransmitters metabolism, while only a reduced effect was observed in reactions involved in glycosphingolipids metabolism. We hypothesize that ARSA deficiency might lead to metabolic consequences that not only compromise the myelin band or the glycosphingolipids metabolism but also the overall metabolic function of the nervous system. Furthermore, these results offer the bases for the design of in-vitro and in-vivo experiments that allow generating new knowledge of MLD pathophysiology and other neurodegenerative diseases.

PMID: 27160716 [PubMed - as supplied by publisher]

Perturbation biology nominates upstream-downstream drug combinations in RAF inhibitor resistant melanoma cells.

Elife. 2015;4

Authors: Korkut A, Wang W, Demir E, Aksoy BA, Jing X, Molinelli EJ, Babur Ö, Bemis DL, Onur Sumer S, Solit DB, Pratilas CA, Sander C

Abstract
Resistance to targeted cancer therapies is an important clinical problem. The discovery of anti-resistance drug combinations is challenging as resistance can arise by diverse escape mechanisms. To address this challenge, we improved and applied the experimental-computational perturbation biology method. Using statistical inference, we build network models from high-throughput measurements of molecular and phenotypic responses to combinatorial targeted perturbations. The models are computationally executed to predict the effects of thousands of untested perturbations. In RAF-inhibitor resistant melanoma cells, we measured 143 proteomic/phenotypic entities under 89 perturbation conditions and predicted c-Myc as an effective therapeutic co-target with BRAF or MEK. Experiments using the BET bromodomain inhibitor JQ1 affecting the level of c-Myc protein and protein kinase inhibitors targeting the ERK pathway confirmed the prediction. In conclusion, we propose an anti-cancer strategy of co-targeting a specific upstream alteration and a general downstream point of vulnerability to prevent or overcome resistance to targeted drugs.

PMID: 26284497 [PubMed - indexed for MEDLINE]

Prioritizing Chemicals for Risk Assessment Using Chemoinformatics: Examples from the IARC Monographs on Pesticides.

Environ Health Perspect. 2016 May 10;

Authors: Guha N, Guyton KZ, Loomis D, Barupal DK

Abstract
BACKGROUND: Identifying cancer hazards is the first step towards cancer prevention. The IARC Monographs Programme, which has evaluated nearly 1000 agents for carcinogenic potential since 1971, typically selects agents for hazard identification on the basis of public nominations, expert advice, published data on carcinogenicity, and public health importance.
OBJECTIVES: Here we present a novel and complementary strategy for identifying agents for hazard evaluation using chemoinformatics, database integration and automated text mining.
DISCUSSION: To inform selection among a broad range of pesticides nominated for evaluation, we identified and screened nearly 6000 relevant chemical structures, thereafter systematically compiled information on 980 pesticides, creating chemical similarity network maps that allowed cluster visualization by chemical similarity, pesticide class, and publicly available information concerning cancer epidemiology, cancer bioassays, and carcinogenic mechanisms. For the IARC Monograph meetings that took place in March and June 2015, this approach supported high priority evaluation of glyphosate, malathion, parathion, tetrachlorvinphos, diazinon, DDT, lindane, and 2,4-D.
CONCLUSIONS: This systematic approach, accounting for chemical similarity and overlaying multiple data sources, can be used by risk assessors as well as researchers to systematize, inform and increase efficiency in selecting and prioritizing agents for hazard identification, risk assessment, regulation or further investigation. This approach could be extended to an array of outcomes and agents, including occupational carcinogens, drugs, and foods.

PMID: 27164621 [PubMed - as supplied by publisher]

Convex biclustering.

Biometrics. 2016 May 10;

Authors: Chi EC, Allen GI, Baraniuk RG

Abstract
In the biclustering problem, we seek to simultaneously group observations and features. While biclustering has applications in a wide array of domains, ranging from text mining to collaborative filtering, the problem of identifying structure in high-dimensional genomic data motivates this work. In this context, biclustering enables us to identify subsets of genes that are co-expressed only within a subset of experimental conditions. We present a convex formulation of the biclustering problem that possesses a unique global minimizer and an iterative algorithm, COBRA, that is guaranteed to identify it. Our approach generates an entire solution path of possible biclusters as a single tuning parameter is varied. We also show how to reduce the problem of selecting this tuning parameter to solving a trivial modification of the convex biclustering problem. The key contributions of our work are its simplicity, interpretability, and algorithmic guarantees-features that arguably are lacking in the current alternative algorithms. We demonstrate the advantages of our approach, which includes stably and reproducibly identifying biclusterings, on simulated and real microarray data.

PMID: 27163413 [PubMed - as supplied by publisher]

BioCreative V CDR task corpus: a resource for chemical disease relation extraction.

Database (Oxford). 2016;2016

Authors: Li J, Sun Y, Johnson RJ, Sciaky D, Wei CH, Leaman R, Davis AP, Mattingly CJ, Wiegers TC, Lu Z

Abstract
Community-run, formal evaluations and manually annotated text corpora are critically important for advancing biomedical text-mining research. Recently in BioCreative V, a new challenge was organized for the tasks of disease named entity recognition (DNER) and chemical-induced disease (CID) relation extraction. Given the nature of both tasks, a test collection is required to contain both disease/chemical annotations and relation annotations in the same set of articles. Despite previous efforts in biomedical corpus construction, none was found to be sufficient for the task. Thus, we developed our own corpus called BC5CDR during the challenge by inviting a team of Medical Subject Headings (MeSH) indexers for disease/chemical entity annotation and Comparative Toxicogenomics Database (CTD) curators for CID relation annotation. To ensure high annotation quality and productivity, detailed annotation guidelines and automatic annotation tools were provided. The resulting BC5CDR corpus consists of 1500 PubMed articles with 4409 annotated chemicals, 5818 diseases and 3116 chemical-disease interactions. Each entity annotation includes both the mention text spans and normalized concept identifiers, using MeSH as the controlled vocabulary. To ensure accuracy, the entities were first captured independently by two annotators followed by a consensus annotation: The average inter-annotator agreement (IAA) scores were 87.49% and 96.05% for the disease and chemicals, respectively, in the test set according to the Jaccard similarity coefficient. Our corpus was successfully used for the BioCreative V challenge tasks and should serve as a valuable resource for the text-mining research community.Database URL: http://www.biocreative.org/tasks/biocreative-v/track-3-cdr/.

PMID: 27161011 [PubMed - in process]

Clinical Management of Head and Neck Cancer Cases: Role of Pharmacogenetics of CYP2 and GSTs.

Oncol Res Treat. 2016;39(4):221-6

Authors: Ruwali M, Dhawan A, Pant MC, Rahman Q, Khurana SM, Parmar D

Abstract
Head and neck squamous cell carcinoma (HNSCC) describes a wide range of malignant tumors which originate in the upper aerodigestive tract and have a multifactorial origin involving both genetic and lifestyle risk factors. The clinical management of head and neck cancer involves surgery, radiotherapy, and chemotherapy. With the advances in treatment strategies for HNSCC, newer targeted therapies are adding to the progress already achieved in the multimodality management of patients although the problems of differences in drug response and adverse drug reactions are still grave concerns. Cancer pharmacogenomics has fast emerged as a new and promising field for the early identification of genetic markers that can predict drug response or toxicity. This could greatly help in identifying genetic markers useful for the selection of optimal drugs, dose, and treatment duration on an individual basis resulting in improved drug efficacy and decreased toxicity. This review focuses on the various treatment modalities available for the clinical management of HNSCC followed by a description of the contribution of genetic variations to chemotherapeutic toxicity and response. Furthermore, studies addressing the association of genetic variants of drug-metabolizing enzymes with treatment response in head and neck cancer are also discussed.

PMID: 27160276 [PubMed - in process]

Recent advances in large-scale protein interactome mapping.

F1000Res. 2016;5

Authors: Mehta V, Trinkle-Mulcahy L

Abstract
Protein-protein interactions (PPIs) underlie most, if not all, cellular functions. The comprehensive mapping of these complex networks of stable and transient associations thus remains a key goal, both for systems biology-based initiatives (where it can be combined with other 'omics' data to gain a better understanding of functional pathways and networks) and for focused biological studies. Despite the significant challenges of such an undertaking, major strides have been made over the past few years. They include improvements in the computation prediction of PPIs and the literature curation of low-throughput studies of specific protein complexes, but also an increase in the deposition of high-quality data from non-biased high-throughput experimental PPI mapping strategies into publicly available databases.

PMID: 27158474 [PubMed]